Search result for Mit introduction to algorithms lectures Online Courses & Certifications
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Autonomous Mobile Robots
by Roland Siegwart , Margarita Chli , Marco Hutter , Davide Scaramuzza- 0.0
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15 Weeks
Basic concepts and algorithms for locomotion, perception, and intelligent navigation. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. This lecture closely follows the textbook Introduction to Autonomous Mobile Robots by Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, second edition 2011....
$50
Getting Started with AWS Machine Learning
by Blaine SundrudTop Instructor- 4.5
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Approx. 9 hours to complete
Introduction to Machine Learning Machine Learning Algorithms Explained Introduction to Amazon Rekognition Introduction to AWS DeepLens Introduction to Amazon Comprehend Introduction to Amazon Comprehend Medical Introduction to Amazon Translate Introduction to Amazon Transcribe Introduction to Amazon SageMaker Introduction to Amazon SageMaker Introduction to Amazon SageMaker GroundTruth Introduction to Amazon SageMaker Neo...
Machine Learning for Accounting with Python
by Linden Lu- 0.0
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Approx. 63 hours to complete
MODULE 1: INTRODUCTION TO MACHINE LEARNING 1 Introduction to Machine Learning 2 Introduction to Data Preprocessing 3 Introduction to Machine Learning Algorithms 1 Introduction to Linear Regression 2 Introduction to Logistic Regression 3 Introduction to Decision Tree 1 Introduction to K-nearest Neighbors 2 Introduction to Support Vector Machine 3 Introduction to Bagging and Random Forest...
Problem Solving Using Computational Thinking
by Chris Quintana- 4.6
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Approx. 11 hours to complete
This course is designed for anyone who is just beginning programming, is thinking about programming or simply wants to understand a new way of thinking about problems critically. Introduction to the Graphic Organizer Introduction to the Graphic Organizer Introduction to Airport Surveillance Case-Study Introduction to Epidemiology Case-Study Introduction to Human Trafficking Case-Study Introduction to the Final Project...
Algorithms, Data Collection, and Starting to Code
by Dr. Tim "Dr. T" Chamillard- 4.6
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Approx. 15 hours to complete
If you’d like to explore how we can interact with the world in a rigorous, computational way, and would also like to start learning to program, this is the course for you! Module 1: Learn about algorithms and write your first C program Module 4: Practice writing C programs to implement STEM computations Algorithms and Starting to Code...
Data Analytics Foundations for Accountancy II
by Robert Brunner- 4.8
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Approx. 70 hours to complete
Module 1: Introduction to Machine Learning Introduction to Module 1 Introduction to Machine Learning Introduction to Linear Regression Introduction to k-nn Introduction to Module 2 Introduction to Fundamental Algorithms Introduction to Logistics Regression Introduction to Decision Trees Introduction to Support Vector Machine Introduction to Module 3 Introduction to Modeling Success Introduction to Bagging...
Quantum Information Science I, Part 2
by Isaac Chuang , Peter Shor- 0.0
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5 Weeks
Have you already taken a foundational introduction to quantum computing course and want to continue with simple quantum protocols and quantum algorithms? This course is part of a three-course series that provides an introduction to the theory and practice of quantum computation. MIT gratefully acknowledges major support for this course, provided by IBM Research....
$49
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Approximation Algorithms
by Mark de Berg- 4.7
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Approx. 15 hours to complete
- O-notation, Ω-notation, Θ-notation; how to analyze algorithms The course notes are there both for students who did not fully understand the lectures as well as for students who would like to dive deeper into the topics. Introduction to Approximation algorithms Introduction to Approximation Algorithms A brief introduction to linear programming...
Unsupervised Learning
by Mark J Grover , Miguel Maldonado- 4.9
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Approx. 9 hours to complete
You will learn several clustering and dimension reduction algorithms for unsupervised learning as well as how to select the algorithm that best suits your data. Introduction to Unsupervised Learning and K Means Introduction to Unsupervised Learning - Part 1 Introduction to Unsupervised Learning - Part 2 Introduction to Clustering Introduction to Unsupervised Learning...
Unsupervised Machine Learning
by Mark J Grover , Miguel Maldonado- 4.8
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Approx. 9 hours to complete
You will learn several clustering and dimension reduction algorithms for unsupervised learning as well as how to select the algorithm that best suits your data. Introduction to Unsupervised Learning and K Means Introduction to Unsupervised Learning - Part 1 Introduction to Unsupervised Learning - Part 2 Introduction to Clustering Introduction to Unsupervised Learning...
